Re: Is OWL useful at all for Quantitative Science?

My sense is that OWL (or any other 'truth'-based knowledge representation
languages) is not that useful for quantitative science (at least not by
itself).  Many of the work-arounds to this shortcoming seem rudimentary at
best:

- Modeling of 'may' in OWL
- Direct incorporation of probability into description logics
- Datatype reasoning
- Increased use of external predicates and function symbols
- Modeling compromises (such as trying to retrofit quantitative concepts
into binary concepts)

This is just my sense of things.
 
----------------------
Chimezie (chee-meh) Thomas-Ogbuji (oh-bu-gee)
Heart and Vascular Institute (Clinical Investigations)
Cleveland Clinic (ogbujic@ccf.org)
Ph.D. Student Case Western Reserve University
(chimezie.thomas-ogbuji@case.edu)


On 3/30/09 9:38 PM, "Oliver Ruebenacker" <curoli@gmail.com> wrote:

>      Hello, All,
> 
>   There recent discussion has made me wonder, whether OWL is at all
> useful to do quantitative science, if we insist that it is used
> correctly (incorrect OWL seems to be useful).
> 
>   Can any one give me a simple example of a useful application of
> correct OWL in quantitative science?
> 
>   I have tried to come up with a simple example. Feel free to come up
> with a simpler one:
> 
>   Express in correct OWL: Washington DC is further away from Boston
> than New York City
> 
>   Use case: I want to fly with my helicopter from Boston to either DC
> or NYC, whichever is closer.
> 
>      Take care
>      Oliver


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Received on Tuesday, 31 March 2009 12:26:47 UTC